SCIR Propagation Model of Public Opinion with Reinforcement Effect in Network

As social networks are gradually affecting people's work and life, studying the rules of online social network communication has become the key to hold the spread of online public opinion in leash. Aiming at the existing public opinion propagation model with the assumption that the immunized users do not propagate the public opinion if they are attached to it, we proposed a public opinion propagation model based on reinforcement effect SCIR network. Based on the SCIR model, we considered the function of social reinforcement effect on users' behavior. When the immunized users see the same information multiple times, there is a certain probability for them to turn to hesitation condition and re-spread. The simulation showed that the proposed model simulates the complexity of public opinion communication in a real-world network and reflects the regulations of public opinion transmission on public social network more accurately.